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논문 상세정보

과학 수업에서 스마트 기기를 활용한 개념 적응적 개별화 학습의 효과

The Effects of Individualized Learning Adapted to Students' Conceptions Using Smart Devices in Science Instruction

초록

이 연구에서는 스마트 기기를 활용한 개념 적응적 개별화 학습의 효과를 개념 이해도, 개념 파지, 학업 성취도, 학습 동기, 과학 수업에 대한 즐거움, 스마트 기기를 활용한 수업에 대한 인식 측면에서 조사하였다. 서울시의 한 남녀 공학 중학교 1학년 4개 학급을 통제 집단과 처치 집단으로 배치하고, 7차시 동안 '분자의 운동'에 대하여 수업을 실시하였다. 이원 공변량 분석 결과, 처치 집단의 개념 검사, 개념 파지검사, 학습 동기 검사, 과학 수업에 대한 즐거움 검사의 점수가 통제집단에 비하여 유의미하게 높았다. 학업 성취도 검사에서는 처치 집단의 점수가 통제 집단보다 높았으나, 그 차이가 통계적으로 유의미하지 않았다. 스마트 기기를 활용한 수업에 대한 학생들의 인식도 긍정적인 것으로 나타났다.

Abstract

In this study, we investigated the effects of individualized learning adapted to students' conceptions using smart devices in science instruction upon students' conceptual understanding, the retention of conception, achievement, learning motivation, enjoyment of science lessons, and perception about individualized learning using smart devices. Four seventh-grade classes at a coed middle school in Seoul were assigned to a control group and a treatment group. Students were taught about molecular motions for seven class periods. Two-way ANCOVA results revealed that the scores of a conception test, the retention of the conception test, a learning motivation test, and an enjoyment of science lessons test for the treatment group were significantly higher than those for the control group. Although the score of the treatment group was higher than that of the control group in the achievement test, the difference was not statistically significant. Students' perceptions about individualized learning using smart devices were also found to be positive.

참고문헌 (37)

  1. Ardac, D., & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students' understanding of chemical change. Journal of Research in Science Teaching, 41(4), 317-337. 
  2. Byrda, K. S., & Caldwell, B. S. (2011). Increased memory load during task completion when procedures are presented on mobile screens. Behaviour & Information Technology, 30(5), 643-658. 
  3. Cho, J. C., & Lim, H. S. (2012). A conceptual model of smart education considering teaching-learning activities and learner's characteristics. Journal of Korean Association of Computer Education, 15(4), 41-49. 
  4. Choi, H. S., Lee, H. K., & Ha, J. C. (2012). The influence of smartphone addiction on mental health, campus life and personal relations - Focusing on K university students. Journal of Korean Data & Information Science Society, 23(5), 1005-1015. 
  5. Fraser, B. J. (1981). Test of science-related attitudes: Handbook. Hawthorn, Australia: The Australian Council for Educational Research. 
  6. FitzPatrick, K. A., Finn, K. E., & Campisi, J. (2011). Effect of personal response systems on student perception and academic performance in courses in a health sciences curriculum. Advances in Physiology Education, 35(3), 280-289. 
  7. Han, J. H., & Finkelstein, A. (2013). Understanding the effects of professors' pedagogical development with clicker assessment and feedback technologies and the impact on students' engagement and learning in higher education. Computers & Education, 65, 64-76. 
  8. Hwang, G. J., & Chang, H. F. (2011). A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Computers & Education, 56(4), 1023-1031. 
  9. Hwang, T. K., & Son, W. K. (2014). Uses of smart devices and their relations to immersion tendency, self-control sbility, and prosocial behavior in preschoolers. Journal of Life-span Studies, 4(1), 69-83. 
  10. Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013). NMC Horizon Report: 2013 Higher Education Edition. The New Media Consortium. 
  11. Joo, J. W., & Lee, Y. H. (2012). A study of possibilities on the photographic education method by smart-phone, especially in social network services. The Society of Korea Photography, 26, 47-60. 
  12. Kang, J., Shim, K. C., Dong. H. K., Gim, W. H., Son, J., Kwack, D. O., Oh, K., & Kim, Y. J. (2014). Practical use of the classroom response system for diagnostic and formative assessments in a high school life science class. Journal of the Korean Association for Science Education, 34(3), 273-283. 
  13. Keller, J. M., & Subhiyah, R. (1993). Course interest survey. Florida State University. 
  14. Kim, B. N. (2013). Effect of smart-phone addiction on youth's sociality development. The Journal of the Korea Contents Association, 4(13), 208-217. 
  15. Kim, K., Chung, K., Cha, J., Kang, Y., & Noh, T. (2007). The effects of situational context feedbacks in chemistry learning with computerassisted instruction. Journal of the Korean Chemical Society, 51(2), 193-200. 
  16. Kim, K., Kang, Y., Kwon, H., Wang, H., & Noh, T. (2006). The effects of CAI adapting to the level of students' conceptual understanding in concept Learning. Journal of Korean Association of Computer Education, 9(2), 79-88. 
  17. Kim, W. H., Seo, J. H., & Kim, Y. J. (2011). A study on the use of ICT in middle school science class. Educational Research, 51, 181-204. 
  18. Kwack, H., & Shin, Y. (2014). The effects of formative assessment using mobile applications on interest and self-directedness in science instruction. Journal of the Korean Association for Science Education, 34(3), 285-294. 
  19. Lee, J. S., & Choi, J. S. (2012). Implementation of application for vocabulary learning through analysis of users needs using smart phone. Journal of Korean Association of Computer Education, 15(1), 43-53. 
  20. Leem, J., & Kim, S. (2013). Effects of individual learning and collaborative learning on academic achievement, self-directed learning skills and social efficacy in smart learning. The Journal of Educational Information and Media, 19(1), 1-24. 
  21. Lim, G. (2011). Research on developing instructional design models for enhancing smart learning. Journal of Korean Association of Computer Education, 14(2), 33-45. 
  22. Ministry of Education, Science, & Technology (2011). Road to powerful nation for human resource development: Action strategies of smart education. Ministry of Education, Science, & Technology. 
  23. Murphy, M. A., & Davidson, G. V.(1991). Computer-based adaptive instruction: Effects of learner control on concept learning. Journal of Computer-Based Instruction, 18(2), 51-54. 
  24. Noh, T., Cha, J., & Kim, C. (1999). The effect of computer-assisted instruction using molecular-level animation and worksheet in high school chemistry class. Journal of the Korean Association for Science Education, 19(1), 128-136. 
  25. Noh, T., Cha, J., Kim, C., & Choi, Y. (1998). The effect of computer-assisted instruction using molecular-level animation in middle school science class. Journal of the Korean Association for Science Education, 18(2), 161-171. 
  26. Noh, T., & Scharmann, L. C. (1997). Instructional influence of a molecularlevel pictorial presentation of matter on students' conceptions and problem-solving ability. Journal of Research in Science Teaching, 34(2), 199-217. 
  27. Ozdemir, S. (2010). Supporting printed books with multimedia: A new way to use mobile technology for learning. British Journal of Educational Technology, 41(6), 135-138. 
  28. Reiser, R., & Dempsey, J. (2006). Trends and issues in instructional design and technology. Upper Saddle River, NJ: Merririll Prentice Hall. 
  29. Ryu, J. (2008). A discourse of implementation the adaptive instructional systems into ubiquitous learning environments, The Korean Journal of Educational Methodology Studies, 20(1), 75-91. 
  30. Shih, J. L., Chuang, C. W., & Hwang, G. J. (2010). An inquiry-based mobile learning approach to enhancing social science learning effectiveness. Educational Technology & Society, 13(4), 50-62. 
  31. Shuler, C., Winters, N., & West, M. (2013). The future of mobile learning: Implications for policy makers and planners. UNESCO Working Paper Series on Mobile Learning. 
  32. Singer, J. E., Wu, H., & Tal, R. (2003). Students' understanding of the particulate nature of matter. School Science and Mathematics, 103(1), 28-44. 
  33. Snir, J., Smith, C. L., & Raz, G. (2003). Linking phenomena with computing underlying models: A software tool for introducing students to the particulate model of matter. Science Education, 87(6), 794-830. 
  34. Song, S. H., & Keller, J. M. (2001). Effectiveness of motivationally adaptive computer-assisted instruction on the dynamic aspects of motivation. Educational Technology, Research & Development, 49(2), 5-22. 
  35. Tomlinson, C. A. (2001). How to differentiate instruction in mixed ability classrooms (2nd ed.). Alexandria, VA: Association for Supervision and Curriculum Development. 
  36. Yang, Y., & Yoo, P. (2003). Analysis of effectiveness of adaptive and non-adaptive web-based learning materials on self-directed learning ability and learning satisfaction: Focus on the korean language at elementary school. The Journal of Elementary Education, 16(2), 443-468. 
  37. Zangyuan, O. (2003). The application of adaptive learning environment on oxidation-reduction web-title. International Journal of Instructional Media, 30(4), 383-405. 

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